Generally, in a wireless communications system, the communications system's capacity may be significantly improved when a transmitter (also referred to as a base station (BS), NodeB, enhanced NodeB, controller, base terminal station, and so forth) has full or partial knowledge of a channel over which it will be transmitting. Information related to the channel may be referred to as channel state information (CSI). CSI may be obtained by the transmitter over a reverse feedback channel. A receiver (also referred to as a mobile station (MS), user, terminal, User Equipment, and so on) of transmissions made by the transmitter may transmit CSI back to the transmitter over the reverse feedback channel. The receiver may estimate the channel, generate the CSI, and feed the CSI back to the transmitter.
However, since CSI feedback consumes communications system bandwidth, there is a desire to minimize the amount of information being fedback to the transmitter. Reducing the amount of information being fedback may involve the use of techniques such as compression, quantization using codebooks, partial information feedback, and so forth.
Usually, codebook quantization makes use of preferably identical codebooks at the transmitter and the receiver. The codebook contains a number of codewords that are representative of the CSI. Instead of feeding back the CSI, the receiver feeds back an index to a codeword in the codebook based a codeword selection function, wherein the codeword selection function typically chooses a codeword that optimizes some criteria in consideration of the CSI.
It has been realized that codebooks should be designed to match the underlying channel characteristics. For example, for SU-MIMO independent identically distributed (iid) Rayleigh fading channels, Grassmannian line/subspace packing (GLP) based codebook has been shown to achieve near optimal performance. On the other hand, those GLP codebooks perform not so well under spatially correlated fading channels, wherein other codebooks have been shown to be relatively more robust, e.g., discrete Fourier transform (DFT) based codebooks and Householder based codebooks, among others. Other examples of codebooks may be complex Hadamard transform (CHT) based codebooks.
Codebook adaptation allows for the adjustment of a base codebook to meet actual communications system operating conditions. Therefore, instead of storing multiple codebooks at both the transmitter and the receiver, which may consume considerable storage space, only a single base codebook may need to be stored at the transmitter and the receiver. The base codebook may be adapted to meet actual communications system operating conditions, which may yield better performance than using statically configured codebooks.